Summary
In this chapter, we've covered the foundational building blocks of the PixieApp programming model that lets you create powerful tools and dashboards directly in the Notebook.
We've also illustrated PixieApp concepts and techniques by showing how to build a GitHub Tracking sample application, including detailed code examples. Best practices and more advanced PixieApp concepts will be covered in Chapter 5, Python and PixieDust Best Practices and Advanced Concepts, including events, streaming, and debugging.
By now, you should hopefully have a good idea of how Jupyter Notebooks, PixieDust, and PixieApps can help bridge the gap between data scientists and developers by enabling them to collaborate from within a single tool, such as Jupyter Notebook.
In the next chapter, we'll show how to free the PixieApp from the Notebook and publish it as a web application using the PixieGateway microservice server.
